Senior Manager, Applied AI

Thermo Fisher

Confirmed live today High trust

Remote

Quick summary

Work type: Remote
Location: North Carolina
Salary: $130,000–$180,000 / yr
Employment: Full-time
Posted: 12 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $204k

This role $155k

$116k $260k

below market most similar roles pay here above market

This role pays less than 80% of similar roles. Most pay $162,000–$246,150 — the blue band above. At the midpoint, this role pays about $155k versus about $204k for comparable roles.

Based on 240 similar postings.

Employer

About Thermo Fisher

Thermo Fisher Scientific is the world leader in serving science, providing analytical instruments, equipment, reagents, consumables, software, and services for life sciences research, pharmaceutical manufacturing, and diagnostics. Industry: Life Sciences & Laboratory Equipment

Thermo Fisher currently has 9 open roles on FindRole.

Listed pay typically runs $95,000–$140,670 across 5 roles with salary data.

Most-posted roles

View all roles at Thermo Fisher

At a glance

TL;DR · Senior Manager, Applied AI

Role Posting Log in to save

JOB TITLE: Senior Manager, Applied AI The Senior Manager, Applied AI provides technical and delivery leadership for a portfolio of artificial intelligence capabilities supporting internal business teams. This role involves translating business needs into scalable capabilities across generative AI, agentic AI, machine learning, and intelligent workflows. You will lead multidisciplinary teams of AI engineers and data scientists to build reusable technical operating models, including platforms, APIs, and architectural patterns. Key responsibilities include overseeing solution architecture, model selection, data integration, and production engineering while ensuring robust evaluation, observability, and governance. Required skills include proficiency in Python, modern AI/ML frameworks, and major cloud platforms like Azure, AWS, or GCP. The work addresses challenges in drug development by creating secure, reliable AI solutions for clinical research and biopharmaceutical data environments.

Skills

Generative AI Large Language Models RAG Machine Learning Python Azure AWS GCP Agentic AI Data Pipelines APIs Observability Data Governance Responsible AI Data Science

What you'll do

Lead a portfolio of applied AI initiatives from opportunity definition through production deployment and continuous improvement.
Translate business needs into scalable capabilities across generative AI, agentic AI, machine learning, and intelligent workflows.
Provide technical leadership and mentorship to multidisciplinary teams of AI engineers and data scientists.
Drive the development of reusable enterprise AI platforms, components, APIs, and architectural patterns.
Design and implement enterprise-grade solutions using LLMs, RAG, AI agents, and orchestration frameworks.
Establish robust AI evaluation, monitoring, and observability practices to ensure production reliability and accuracy.
Embed governance, security, and responsible AI practices throughout the entire AI solution lifecycle.
Define technical standards and reference architectures for model selection, data architecture, and lifecycle management.

What we're looking for

Bachelor's degree with 8-10 years of experience in AI, machine learning, data science, software engineering, or a related field.
Advanced degree with 7 years of relevant experience in AI, machine learning, data science, software engineering, or a related field.
Demonstrated experience leading AI or machine learning teams and complex technology portfolios in an enterprise environment.
Proven experience taking AI solutions from concept through production deployment and operation at enterprise scale.
Strong understanding of generative AI, LLMs, RAG, agentic workflows, and modern AI architecture.
Experience with major cloud and AI platforms such as Azure, AWS, or GCP.
Working knowledge of Python and modern AI/ML development frameworks.
Experience operating within data governance, security, privacy, regulatory, and responsible AI frameworks.
Experience managing external technology partners, consultants, or distributed delivery teams.
Life sciences or clinical research industry experience (preferred).
Ability to pass a comprehensive background check, including a drug screening.

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